net.sourceforge.openforecast.tests
Class BasicTest
- java.lang.Object
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- junit.framework.Assert
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- junit.framework.TestCase
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- net.sourceforge.openforecast.tests.OpenForecastTestCase
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- net.sourceforge.openforecast.tests.BasicTest
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- All Implemented Interfaces:
- junit.framework.Test
public class BasicTest extends OpenForecastTestCase
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Constructor Summary
Constructors Constructor and Description BasicTest(java.lang.String name)
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method and Description voidtestDataPoint()Tests that two DataPoint objects initialized differently but with the same data are equal.voidtestForecast()Creates a simple data set where the dependent value is exactly the same as the independent value, then tests the chosen forecast model on five further values in the series.voidtestUnknownVariableInObservation()Tests that an IllegalArgumentException is thrown if an attempt is made to retrieve the value of an unknown independent variable.-
Methods inherited from class junit.framework.TestCase
assertEquals, assertEquals, assertEquals, assertEquals, assertEquals, assertEquals, assertEquals, assertEquals, assertEquals, assertEquals, assertEquals, assertEquals, assertEquals, assertEquals, assertEquals, assertEquals, assertEquals, assertEquals, assertEquals, assertEquals, assertFalse, assertFalse, assertNotNull, assertNotNull, assertNotSame, assertNotSame, assertNull, assertNull, assertSame, assertSame, assertTrue, assertTrue, countTestCases, fail, fail, failNotEquals, failNotSame, failSame, format, getName, run, run, runBare, setName, toString
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Method Detail
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testDataPoint
public void testDataPoint()
Tests that two DataPoint objects initialized differently but with the same data are equal.
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testUnknownVariableInObservation
public void testUnknownVariableInObservation()
Tests that an IllegalArgumentException is thrown if an attempt is made to retrieve the value of an unknown independent variable.
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testForecast
public void testForecast()
Creates a simple data set where the dependent value is exactly the same as the independent value, then tests the chosen forecast model on five further values in the series. A regression model should give accurate results for this series, whereas a moving average would always lag the value (so not be as appropriate).
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